Synopses & Reviews
Computational Surface and Roundness Metrology provides an extraordinarily practical and hands-on approach towards understanding the diverse array of mathematical methods used in surface texture and roundness analysis. The book, in combination with a mathematical package or programming language interface, provides an invaluable tool for experimenting, learning, and discovering the many flavors of mathematics that are so routinely taken for granted in metrology. Whether the objective is to understand the origin of that ubiquitous transmission characteristics curve of a filter we see so often yet do not quite comprehend, or to delve into the intricate depths of a deceptively simple problem of fitting a line or a plane to a set of points, Computational Surface and Roundness Metrology describes it all (in exhaustive detail) using examples, illustrations, exercises, and a link to some of the finest publications in the field for over half a century. From the graduate student of metrology to the practicing engineer on the shop floor, Computational Surface and Roundness Metrology is a must-have reference for all involved in metrology, instrumentation/optics, manufacturing, and electronics.
Review
Computational Surface and Roundness Metrology can be used for final-year undergraduate engineering courses (for example, manufacturing, mechanical, etc.) or as a subject on manufacturing at postgraduate level. Also, this book can serve as a useful reference for academics, manufacturing researchers, mechanical and manufacturing engineers, and professionals in related industries with manufacturing, quality, and surface and roundness metrology. J. Paul Davim (from the International Journal of Mechatronics and Manufacturing Systems)
Synopsis
This book provides an extraordinarily practical and hands-on approach towards understanding the diverse array of mathematical methods used in surface texture and roundness analysis. There are examples, illustrations and exercises included.
About the Author
Bala Muralikrishnan has a PhD in Mechanical Engineering from the University of North Carolina at Charlotte, USA. He works for the National Institute of Standards and Technology, where he is a guest researcher in the Engineering Metrology Group of the Precision Engineering Division - one of the divisions of the Manufacturing Engineering Laboratory. Jayaraman Raja has a PhD in Mechanical Engineering from the Indian Institute of Technology, Madras, India. He is a professor and chairman in the Department of Mechanical Engineering & Engineering Science at the University of North Carolina at Charlotte, USA. His research interests include Surface & Form Metrology; Computational Metrology; and Precision Engineering.
Table of Contents
Introduction Part I: Filtering A Brief History of Filtering Filtering in Frequency Domains Time Domain Filtering Gaussian Filter 2RC Filter Filtering Roundness Profiles Filtering 3D Surfaces Part II: Advanced Filtering Gaussian Regression Filters Spline Filter Robust Filters Envelope and Morphological Filters Multi-scale Filtering Part III: Fitting Introduction to Fitting Substitute Geometry Least-squares Best Fit Line and Plane Non-linear Least-squares I: Introduction Non-linear Least-squares II: Circle, Sphere and Cylinder Fitting Radius Suppressed Circle Data Exchange Algorithms for Minimum Zone Reference Circle Fitting using Linear Programming Simplex Part IV: Parameterization Surface Texture Parameters I: Amplitude, Spacing, Hybrid and Shape Surface Texture Parameters II: Autocorrelation, Power Spectral Density, Bearing Area 3D Surface Texture Parameters Part V: Errors and Uncertainty Uncertainty Considerations Uncertainty Propagation in Computations Error Separation Techniques in Roundness Metrology Other Relevant Topics