Neural Calibration of Coordinate Measuring Arms
Springer Nature
This book presents a groundbreaking fusion of classical metrological modelling and modern artificial intelligence to dramatically enhance the accuracy of geometric measurements in industrial environments. Designed for researchers, engineers, and practitioners in precision measurement and power equipment manufacturing, this book offers a comprehensive and rigorously validated methodology for compensating both kinematic and non kinematic errors in coordinate measuring arms (CMAs). At the core of the work is a universal calibration strategy that employs three reference standards within a single procedure. This innovative approach enables the simultaneous assessment of systematic sensing errors, point reproducibility, and linear movement stability—capabilities rarely addressed together in existing calibration methods. Building on this foundation, this book introduces a single point polynomial correction model that achieves a fourfold reduction in residual kinematic errors, offering a practical and efficient enhancement to traditional calibration techniques. This book’s most distinctive contribution lies in its application of artificial neural networks to compensate for destabilising…
