Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/1657
Title: A fibre optic sensor for the measurement of surface roughness and displacement using artificial neural networks
Authors: Zhang, K
Butler, C
Yang, QP
Lu, Y
Keywords: Artificial neural network;Displacement;Fiber optic sensor;Measurement;Surface roughness
Issue Date: 1997
Publisher: IEEE
Citation: IEEE Transactions on Instrumentation and Measurement. 46 (4): 899-902
Abstract: This paper presents a fiber optic sensor system, artificial neural networks (fast back-propagation) are employed for the data processing. The use of the neural networks makes it possible for the sensor to be used both for surface roughness and displacement measurement at the same time. The results indicate 100% correct surface classification for ten different surfaces (different materials, different manufacturing methods, and different surface roughnesses) and displacement errors less then ±5 μm. The actual accuracy was restricted by the calibration machine. A measuring range of ±0.8 mm for the displacement measurement was achieved.
URI: http://bura.brunel.ac.uk/handle/2438/1657
ISSN: 0018-9456
Appears in Collections:Advanced Manufacturing and Enterprise Engineering (AMEE)
Dept of Mechanical Aerospace and Civil Engineering Research Papers



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