Application of neural networks for surface roughness measurement in finish turning. (English) Zbl 0912.90169
Summary: A laser system which incorporates a charge-coupled-device sensor is developed to measure, in real time, the maximum peak-to-valley surface roughness, \(R_{\max}\), produced during finish turning. A three-layer neural network is used in conjunction with a back-propagation learning algorithm to predict \(R_{\max}\) by quickly recognizing the angular scattered light patterns reflected from the workpiece in the feed direction. The predicted \(R_{\max}\) values have a maximum error of about 10% when compared to conventional stylus measurements.
Keywords:
laser system; maximum peak-to-valley surface roughness; three-layer neural network; back-propagation learning algorithmReferences:
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