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A fibre optic sensor for the measurement of surface roughness and displacement using artificial neural networks

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4 Author(s)
Zhang, K. ; Centre for Manuf. Metrol., Brunel Univ., Uxbridge, UK ; Butler, C. ; Yang, Q. ; Lu, Y.

This paper presents a fibre optic sensor system. Artificial neural networks using fast backpropagation 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 were achieved

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Instrumentation and Measurement Technology Conference, 1996. IMTC-96. Conference Proceedings. Quality Measurements: The Indispensable Bridge between Theory and Reality., IEEE  (Volume:2 )

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