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BP Neural Network for AACMM Error Compensation by Mokrane is a document available to read on EtoBox.

This research article presents a modeling and error compensation method for articulated arm coordinate measuring machines (AACMM) using Back-Propagation Neural Networks (BPNN). The proposed method aims to improve the accuracy of AACMM by compensating for various error factors through a neural network model that utilizes joint angles as input and probe coordinates as output. Experimental results demonstrate that the method can effectively eliminate up to 97% of measurement errors, showcasing its effectivenes

Author

Mokrane

Language

EN