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Computational Surface and Roundness Metrology
 
 
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Computational Surface and Roundness Metrology [Hardcover]

Balasubramanian Muralikrishnan (Author), Jayaraman Raja (Author)

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Book Description

1848002963 978-1848002968 November 25, 2008 2nd Printing.
“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, this book describes it all (in exhaustive detail). From the graduate student of metrology to the practicing engineer on the shop floor, this book is a must-have reference for all involved in metrology, instrumentation/optics, manufacturing, and electronics.

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Editorial Reviews

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)

From the Back Cover

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.

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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
surface finish parameters, surface roughness, limaçon approximation, envelope mean line, filtering surface profiles, part form error, waviness profile, amplitude transmission characteristics, regression filter, roundness instrument, roundness analysis, computational surface, surface texture data, surface texture analysis, roundness profile, spindle error, spline filter, roundness data, surface texture parameters, filtered profile, modified weighting function, raw profile, substitute geometry, surface metrology, alternating rule
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, American Society of Mechanical Engineers, Precision Engineering, Non-linear Least-Squares, Von Weingraber, Journal of Physics, Power Spectral Density, Upper Saddle River, Scientific Instruments, Prentice Hall, Filtering Roundness Profiles, Profile Method, Geometrical Product Specifications, Chemnitz University of Technology, International Colloquium, Physical Laboratory, Reference Circle-Fitting Using Linear Programming Simplex, Gaussian Regression Filters, Engineering Optimization, Kogan Page Science, Fitting Radius-Suppressed Circle Data, Least-Squares Best-Fit Geometric Elements, Rank Taylor Hobson, Frequency-Domain Filtering, Manufacturing Review
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Front Cover | Table of Contents | First Pages | Index | Surprise Me!
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