Well written textbook on industrial applications of Statistical Measurement Theory. It deals with the principal issues of measurement theory, is concise and intelligibly written, and to a wide extent self-contained. Difficult theoretical issues are separated from the mainstream presentation. Each topic starts with an informal introduction followed by an example, the rigorous problem formulation, solution method, and a detailed numerical solution. Chapter are concluded with a set of exercises of increasing difficulty, mostly with solutions. Knowledge of calculus and fundamental probability and statistics is assumed.

Well written textbook on industrial applications of Statistical Measurement Theory. It deals with the principal issues of measurement theory, is concise and intelligibly written, and to a wide extent self-contained. Difficult theoretical issues are separated from the mainstream presentation. Each topic starts with an informal introduction followed by an example, the rigorous problem formulation, solution method, and a detailed numerical solution. Chapter are concluded with a set of exercises of increasing difficulty, mostly with solutions. Knowledge of calculus and fundamental probability and statistics is assumed.

The expression of uncertainty in measurement poses a challenge since it involves physical, mathematical, and philosophical issues. This problem is intensified by the limitations of the probabilistic approach used by the current standard (the GUM Instrumentation Standard). This text presents an alternative approach. It makes full use of the mathematical theory of evidence to express the uncertainty in measurements. Coverage provides an overview of the current standard, then pinpoints and constructively resolves its limitations. Numerous examples throughout help explain the book’s unique approach.

Theory and Design for Mechanical Measurements merges time-tested pedagogy with current technology to deliver an immersive, accessible resource for both students and practicing engineers. Emphasizing statistics and uncertainty analysis with topical integration throughout, this book establishes a strong foundation in measurement theory while leveraging the e-book format to increase student engagement with interactive problems, electronic data sets, and more. This new Seventh edition has been updated with new practice problems, electronically accessible solutions, and dedicated Instructor Problems that ease course planning and assessment. Extensive coverage of device selection, test procedures, measurement system performance, and result reporting and analysis sets the field for generalized understanding, while practical discussion of data acquisition hardware, infrared imaging, and other current technologies demonstrate real-world methods and techniques. Designed to align with a variety of undergraduate course structures, this unique text offers a highly flexible pedagogical framework while remaining rigorous enough for use in graduate studies, independent study, or professional reference.

This is a graduate text introducing the fundamentals of measure theory and integration theory, which is the foundation of modern real analysis. The text focuses first on the concrete setting of Lebesgue measure and the Lebesgue integral (which in turn is motivated by the more classical concepts of Jordan measure and the Riemann integral), before moving on to abstract measure and integration theory, including the standard convergence theorems, Fubini's theorem, and the Carathéodory extension theorem. Classical differentiation theorems, such as the Lebesgue and Rademacher differentiation theorems, are also covered, as are connections with probability theory. The material is intended to cover a quarter or semester's worth of material for a first graduate course in real analysis. There is an emphasis in the text on tying together the abstract and the concrete sides of the subject, using the latter to illustrate and motivate the former. The central role of key principles (such as Littlewood's three principles) as providing guiding intuition to the subject is also emphasized. There are a large number of exercises throughout that develop key aspects of the theory, and are thus an integral component of the text. As a supplementary section, a discussion of general problem-solving strategies in analysis is also given. The last three sections discuss optional topics related to the main matter of the book.

Adhesion Measurement Methods: Theory and Practice provides practical information on the most important measurement techniques, their unique advantages and disadvantages, and the selection of the proper method for a given application. It includes useful information and formulae on adhesion related matters such as driving force formulae for various m

Market_Desc: · Mechanical Engineers Special Features: · Detailed examples with consistent methodology illustrate use of new material as it is discussed· Condensed but thorough coverage of statistical analysis of data teaches readers how to analyze and report data using just a handful of statistical tools and concepts About The Book: This textbook provides an in-depth introduction to the theory of engineering measurements, measurement system performance, and instrumentation. Uncertainty analysis is introduced and developed for both the beginner and the advanced engineer. The book also offers an extended discussion of sampling concepts, analog-to-digital interfacing, signal conditioning and data acquisition.